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Title: :  Handwritten Signature Verification System using machine Learning Approach
PaperId: :  14672
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 7 Issue 3 2021
DUI:    16.0415/IJARIIE-14672
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Pooja GaikwadMET’s Institute of Engineering, Nashik
Kashaf PathanMET’s Institute of Engineering, Nashik
Purva PatilMET’s Institute of Engineering, Nashik
Prof. R.P. Dahake5MET’s Institute of Engineering, Nashik
Laxmi PagareMET’s Institute of Engineering, Nashik

Abstract

Information Technology
Offline handwritten signature, classification, algorithms, artificial intelligence, CNN
In the field of biometric, offline handwritten signature verification is most referenced procedure for authentication of a person during financial transaction. A signature is the “seal of approval” for verifying the approval of a person and remains the most preferred means of verification. This verification system mainly aims at verifying the discriminating the forged signature from the genuine signatures. In this work, Convolutional Neural Networks (CNN) have been used to learn features from the pre-processed genuine signatures and forged signatures dataset. The CNN used is inspired by Inception V1 architecture (GoogleNet). The architecture uses the concept of having different filters on same level so that the network would be wider instead of deeper. In this paper, the proposed model is tested on few publicly available datasets on kaggle.com. has been successful in verifying handwritten signature images provided with an extensive precision level.

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IJARIIE Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, and Laxmi Pagare. "Handwritten Signature Verification System using machine Learning Approach" International Journal Of Advance Research And Innovative Ideas In Education Volume 7 Issue 3 2021 Page 3284-3289
MLA Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, and Laxmi Pagare. "Handwritten Signature Verification System using machine Learning Approach." International Journal Of Advance Research And Innovative Ideas In Education 7.3(2021) : 3284-3289.
APA Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, & Laxmi Pagare. (2021). Handwritten Signature Verification System using machine Learning Approach. International Journal Of Advance Research And Innovative Ideas In Education, 7(3), 3284-3289.
Chicago Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, and Laxmi Pagare. "Handwritten Signature Verification System using machine Learning Approach." International Journal Of Advance Research And Innovative Ideas In Education 7, no. 3 (2021) : 3284-3289.
Oxford Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, and Laxmi Pagare. 'Handwritten Signature Verification System using machine Learning Approach', International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 3, 2021, p. 3284-3289. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Handwritten_Signature_Verification_System_using_machine_Learning_Approach_ijariie14672.pdf (Accessed : ).
Harvard Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, and Laxmi Pagare. (2021) 'Handwritten Signature Verification System using machine Learning Approach', International Journal Of Advance Research And Innovative Ideas In Education, 7(3), pp. 3284-3289IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Handwritten_Signature_Verification_System_using_machine_Learning_Approach_ijariie14672.pdf (Accessed : )
IEEE Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, and Laxmi Pagare, "Handwritten Signature Verification System using machine Learning Approach," International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 3, pp. 3284-3289, May-Jun 2021. [Online]. Available: https://ijariie.com/AdminUploadPdf/Handwritten_Signature_Verification_System_using_machine_Learning_Approach_ijariie14672.pdf [Accessed : ].
Turabian Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, and Laxmi Pagare. "Handwritten Signature Verification System using machine Learning Approach." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 7 number 3 ().
Vancouver Pooja Gaikwad, Kashaf Pathan, Purva Patil, Prof. R.P. Dahake5, and Laxmi Pagare. Handwritten Signature Verification System using machine Learning Approach. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2021 [Cited : ]; 7(3) : 3284-3289. Available from: https://ijariie.com/AdminUploadPdf/Handwritten_Signature_Verification_System_using_machine_Learning_Approach_ijariie14672.pdf
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